Overview

Dataset statistics

Number of variables6
Number of observations1000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory47.0 KiB
Average record size in memory48.1 B

Variable types

Numeric6

Alerts

C/A is highly overall correlated with Mn and 1 other fieldsHigh correlation
Mn is highly overall correlated with C/A and 1 other fieldsHigh correlation
PDI is highly overall correlated with POX/CHigh correlation
POX/C is highly overall correlated with PDIHigh correlation
POX/M is highly overall correlated with MnHigh correlation
X is highly overall correlated with C/AHigh correlation
POX/C has unique valuesUnique
C/A has unique valuesUnique
POX/M has unique valuesUnique
X has unique valuesUnique
PDI has unique valuesUnique
Mn has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:04:06.752885
Analysis finished2024-03-14 00:04:12.138870
Duration5.39 seconds
Software versionydata-profiling vv4.6.5
Download configurationconfig.json

Variables

POX/C
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean144.31861
Minimum90.909091
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-13T21:04:12.265567image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum90.909091
5-th percentile116.63637
Q1132.94685
median144.33252
Q3155.67973
95-th percentile172.03977
Maximum200
Range109.09091
Interquartile range (IQR)22.732875

Descriptive statistics

Standard deviation16.880969
Coefficient of variation (CV)0.11697015
Kurtosis-0.02665933
Mean144.31861
Median Absolute Deviation (MAD)11.392887
Skewness0.004079331
Sum144318.61
Variance284.96712
MonotonicityNot monotonic
2024-03-13T21:04:12.471313image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0668847 1
 
0.1%
145.0829309 1
 
0.1%
163.3507459 1
 
0.1%
147.0481316 1
 
0.1%
164.0004918 1
 
0.1%
115.7533967 1
 
0.1%
149.9821804 1
 
0.1%
151.7046537 1
 
0.1%
114.0898242 1
 
0.1%
133.3116111 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
90.90909091 1
0.1%
93.68727904 1
0.1%
97.16528533 1
0.1%
98.84349409 1
0.1%
100.0845138 1
0.1%
101.2138492 1
0.1%
102.7333618 1
0.1%
103.4003799 1
0.1%
103.9057908 1
0.1%
104.7996913 1
0.1%
ValueCountFrequency (%)
200 1
0.1%
195.836886 1
0.1%
191.8511391 1
0.1%
189.3555627 1
0.1%
188.5013372 1
0.1%
187.2308636 1
0.1%
186.0548743 1
0.1%
185.7724382 1
0.1%
184.3077447 1
0.1%
184.1358495 1
0.1%

C/A
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.11847689
Minimum0.025
Maximum0.22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-13T21:04:12.740563image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0.025
5-th percentile0.070883215
Q10.098979303
median0.11844542
Q30.13796221
95-th percentile0.16584282
Maximum0.22
Range0.195
Interquartile range (IQR)0.038982906

Descriptive statistics

Standard deviation0.02896727
Coefficient of variation (CV)0.24449721
Kurtosis-0.00013490001
Mean0.11847689
Median Absolute Deviation (MAD)0.019518894
Skewness0.0045588414
Sum118.47689
Variance0.00083910271
MonotonicityNot monotonic
2024-03-13T21:04:12.930058image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1309863058 1
 
0.1%
0.1720202696 1
 
0.1%
0.1131752478 1
 
0.1%
0.1306141805 1
 
0.1%
0.07831105352 1
 
0.1%
0.06549399871 1
 
0.1%
0.1794428717 1
 
0.1%
0.1258356997 1
 
0.1%
0.1158224977 1
 
0.1%
0.08631714299 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
0.025 1
0.1%
0.0304113615 1
0.1%
0.03672064228 1
0.1%
0.03918497954 1
0.1%
0.04279922505 1
0.1%
0.04512005371 1
0.1%
0.04709442114 1
0.1%
0.0474207899 1
0.1%
0.04977593697 1
0.1%
0.05109712931 1
0.1%
ValueCountFrequency (%)
0.22 1
0.1%
0.2025468346 1
0.1%
0.1984406953 1
0.1%
0.1964829435 1
0.1%
0.1952468759 1
0.1%
0.1919684995 1
0.1%
0.1906857951 1
0.1%
0.1892182141 1
0.1%
0.1872116089 1
0.1%
0.1866696008 1
0.1%

POX/M
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001454052
Minimum0.000831429
Maximum0.002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-13T21:04:13.139497image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0.000831429
5-th percentile0.0011702986
Q10.0013378531
median0.0014541444
Q30.0015705094
95-th percentile0.0017379874
Maximum0.002
Range0.001168571
Interquartile range (IQR)0.00023265626

Descriptive statistics

Standard deviation0.00017269564
Coefficient of variation (CV)0.11876854
Kurtosis0.0070253818
Mean0.001454052
Median Absolute Deviation (MAD)0.00011650578
Skewness-0.014323155
Sum1.454052
Variance2.9823784 × 10-8
MonotonicityNot monotonic
2024-03-13T21:04:13.351963image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.001436623456 1
 
0.1%
0.001060824282 1
 
0.1%
0.001620593811 1
 
0.1%
0.001354544091 1
 
0.1%
0.001546232503 1
 
0.1%
0.000831429 1
 
0.1%
0.001592451802 1
 
0.1%
0.001332547323 1
 
0.1%
0.001589109008 1
 
0.1%
0.001560519623 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
0.000831429 1
0.1%
0.0009342051028 1
0.1%
0.0009672779537 1
0.1%
0.0009925032256 1
0.1%
0.00100927487 1
0.1%
0.001014111025 1
0.1%
0.001022983167 1
0.1%
0.001038098451 1
0.1%
0.001040853278 1
0.1%
0.001051836304 1
0.1%
ValueCountFrequency (%)
0.002 1
0.1%
0.001955738912 1
0.1%
0.001949505357 1
0.1%
0.00191535218 1
0.1%
0.00190395122 1
0.1%
0.001895405973 1
0.1%
0.001886300902 1
0.1%
0.001876707079 1
0.1%
0.001865638919 1
0.1%
0.00185781745 1
0.1%

X
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.68545205
Minimum0.53506242
Maximum0.91100748
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-13T21:04:13.539438image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0.53506242
5-th percentile0.60997333
Q10.65056322
median0.68300846
Q30.71496441
95-th percentile0.77443192
Maximum0.91100748
Range0.37594506
Interquartile range (IQR)0.064401197

Descriptive statistics

Standard deviation0.050885809
Coefficient of variation (CV)0.074236862
Kurtosis0.86327772
Mean0.68545205
Median Absolute Deviation (MAD)0.032064544
Skewness0.54316729
Sum685.45205
Variance0.0025893655
MonotonicityNot monotonic
2024-03-13T21:04:13.733947image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6754157404 1
 
0.1%
0.5720696681 1
 
0.1%
0.688840558 1
 
0.1%
0.6542870346 1
 
0.1%
0.7487879389 1
 
0.1%
0.7445375051 1
 
0.1%
0.6115959946 1
 
0.1%
0.6551776062 1
 
0.1%
0.713289601 1
 
0.1%
0.7527358889 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
0.5350624212 1
0.1%
0.5504530675 1
0.1%
0.5618976216 1
0.1%
0.5678749894 1
0.1%
0.5680774178 1
0.1%
0.5720696681 1
0.1%
0.5787676628 1
0.1%
0.5803873801 1
0.1%
0.5852542549 1
0.1%
0.5859471592 1
0.1%
ValueCountFrequency (%)
0.9110074787 1
0.1%
0.8889685875 1
0.1%
0.8679051001 1
0.1%
0.8582428739 1
0.1%
0.8576189315 1
0.1%
0.8515135341 1
0.1%
0.8426440384 1
0.1%
0.8356958213 1
0.1%
0.83361774 1
0.1%
0.8321809153 1
0.1%

PDI
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0311085
Minimum1.0278006
Maximum1.0593777
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-13T21:04:13.914211image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum1.0278006
5-th percentile1.0287703
Q11.0297702
median1.030688
Q31.0318541
95-th percentile1.0345165
Maximum1.0593777
Range0.031577067
Interquartile range (IQR)0.0020838284

Descriptive statistics

Standard deviation0.0022905659
Coefficient of variation (CV)0.0022214596
Kurtosis35.432756
Mean1.0311085
Median Absolute Deviation (MAD)0.0010078104
Skewness4.1582999
Sum1031.1085
Variance5.246692 × 10-6
MonotonicityNot monotonic
2024-03-13T21:04:14.150545image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.028852994 1
 
0.1%
1.031793774 1
 
0.1%
1.030978661 1
 
0.1%
1.030146578 1
 
0.1%
1.032243733 1
 
0.1%
1.037159047 1
 
0.1%
1.030671031 1
 
0.1%
1.030686769 1
 
0.1%
1.029233019 1
 
0.1%
1.031244161 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
1.027800633 1
0.1%
1.027852798 1
0.1%
1.027867157 1
0.1%
1.028011181 1
0.1%
1.02803256 1
0.1%
1.028054481 1
0.1%
1.02813225 1
0.1%
1.028162438 1
0.1%
1.028169533 1
0.1%
1.028169591 1
0.1%
ValueCountFrequency (%)
1.059377699 1
0.1%
1.05244385 1
0.1%
1.046915388 1
0.1%
1.044379218 1
0.1%
1.043920553 1
0.1%
1.043158656 1
0.1%
1.04030156 1
0.1%
1.039675586 1
0.1%
1.039115159 1
0.1%
1.039108215 1
0.1%

Mn
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51530.717
Minimum33473.644
Maximum99889.759
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-13T21:04:14.400875image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum33473.644
5-th percentile41970.111
Q146792.778
median50713.347
Q355345.662
95-th percentile64122.68
Maximum99889.759
Range66416.115
Interquartile range (IQR)8552.8841

Descriptive statistics

Standard deviation6958.5414
Coefficient of variation (CV)0.13503677
Kurtosis2.9986077
Mean51530.717
Median Absolute Deviation (MAD)4311.2966
Skewness1.0322096
Sum51530717
Variance48421298
MonotonicityNot monotonic
2024-03-13T21:04:14.603336image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50658.64639 1
 
0.1%
57447.84631 1
 
0.1%
45611.3567 1
 
0.1%
51790.30771 1
 
0.1%
52584.23521 1
 
0.1%
99889.7587 1
 
0.1%
40879.84779 1
 
0.1%
52713.51495 1
 
0.1%
48786.92532 1
 
0.1%
52686.34536 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
33473.64402 1
0.1%
37497.83683 1
0.1%
37557.37724 1
0.1%
37994.72351 1
0.1%
38010.92935 1
0.1%
38332.90934 1
0.1%
38463.42347 1
0.1%
38665.0368 1
0.1%
38712.93689 1
0.1%
39015.90306 1
0.1%
ValueCountFrequency (%)
99889.7587 1
0.1%
79785.31767 1
0.1%
79048.91427 1
0.1%
78457.88414 1
0.1%
76430.63684 1
0.1%
75044.54197 1
0.1%
74938.23813 1
0.1%
74930.42692 1
0.1%
74582.50714 1
0.1%
73469.29111 1
0.1%

Interactions

2024-03-13T21:04:11.027282image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:06.855661image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:07.651529image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:08.476948image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:09.353643image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:10.189580image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:11.170898image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:06.991248image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:07.779151image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:08.675423image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:09.482264image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:10.325539image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:11.334461image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:07.138541image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:07.929748image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:08.809551image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:09.625882image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:10.482622image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:11.471095image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:07.274535image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:08.066417image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:08.940746image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:09.762515image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:10.627495image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:11.611721image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:07.404157image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:08.208004image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:09.085328image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:09.897353image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:10.761468image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:11.750849image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:07.530840image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:08.341220image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:09.220963image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:10.038942image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-13T21:04:10.887688image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Correlations

2024-03-13T21:04:14.726039image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
C/AMnPDIPOX/CPOX/MX
C/A1.000-0.573-0.430-0.013-0.002-0.920
Mn-0.5731.0000.316-0.155-0.7660.366
PDI-0.4300.3161.0000.634-0.1980.182
POX/C-0.013-0.1550.6341.000-0.012-0.235
POX/M-0.002-0.766-0.198-0.0121.0000.256
X-0.9200.3660.182-0.2350.2561.000

Missing values

2024-03-13T21:04:11.915989image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:04:12.070055image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

POX/CC/APOX/MXPDIMn
0127.0668850.1309860.0014370.6754161.02885350658.646392
1140.3152790.1077080.0012380.6842341.03052059674.301485
2137.2519110.0965950.0012810.7106951.03081260219.372697
3134.1137510.1172530.0015200.6956891.02944149400.873103
4163.7905780.1127310.0017660.6980161.03068242424.024049
5132.9905220.0594590.0014990.8112361.03672860333.109730
6126.9745420.1545650.0012630.6323461.02899453691.442367
7120.1162060.1475830.0013810.6551361.02838551037.181235
8130.6640750.1239890.0012300.6664011.03028058421.019930
9136.4978680.1321530.0013580.6610461.02949852297.434261
POX/CC/APOX/MXPDIMn
990104.7996910.1210890.0013630.7009951.02930756018.010656
991158.9484480.0625290.0014710.7849461.03430758611.719217
992123.5273440.0574580.0015930.8260511.03795058294.491749
993128.2543670.1307180.0013070.6656481.02911354874.698538
994137.2936450.1521940.0018660.6620291.02969037994.723509
995146.2709310.1341240.0012690.6418541.03109654201.338756
996136.8313590.1401400.0012480.6402001.02976855026.316024
997149.0614830.1572160.0013990.6223801.03124147480.431021
998157.5401660.1209730.0014690.6697261.03077148876.869906
999170.3452500.1555310.0012440.5900591.03451150435.916510